The invention relates generally to imaging systems, and more particularly, embodiments relate to a method and system for correcting scatter generated by a multi-modality imaging system.
Multi-modality imaging systems exist that scan using different modalities, such as, for example, Positron Emission Tomography (PET), Single Photon Emission Computed Tomography (SPECT), and Computed Tomography (CT). During operation of a PET imaging system, for example, a patient is initially injected with a radiopharmaceutical that emits positrons as the radiopharmaceutical decays. The emitted positrons travel a relatively short distance before the positrons encounter an electron, at which point an annihilation occurs whereby the electron and positron are annihilated and converted into two gamma photons each having an energy of 511 keV.
The annihilation events are typically identified by a time coincidence between the detection of the two 511 keV gamma photons in the two oppositely disposed detectors, i.e., the gamma photon emissions are detected virtually simultaneously by each detector. When two oppositely disposed gamma photons each strike an oppositely disposed detector to produce a time coincidence, gamma photons also identify a line of response, or LOR, along which the annihilation event has occurred.
The number of time coincidences, generally referred to as coincidence events, detected within a field of view (FOV) of the detector is the count rate of the detector. The count rate at each of two oppositely disposed detectors is generally referred to as singles counts, or singles. The coincidence event is identified if the time difference between the arrivals of signals at the oppositely disposed detectors is less than a predetermined time coincidence. The number of coincidence events per second registered is commonly referred to as prompt coincidences or prompts. Prompts may include true, random, and scatter coincidence events.
True coincidences are those physically correlated time coincidences, i.e., two gamma photons emitted in the process of annihilation or photons produced from the two primary gamma photons. Random coincidences are events that arise from the essentially simultaneous detection of two photons that arise from two different annihilation events that occur at nearly the same time. Scatter coincidence events occur because some gamma rays are deflected from their original direction due to interaction with a body part before reaching the detectors. It is desirable to reject the scatter events during the acquisition of emission sinograms, because the images generated using only the detected true coincidence events represent a true activity distribution of radio-activity in the scanned body part of the patient. Moreover, scattered radiations increase the background to the image, thus degrading the image contrast.
One conventional method to correct for scatter includes identifying the counts just outside the boundary of the patient, where no true coincidence counts are expected. The outside counts contain both random and scatter events. After subtracting random counts, the scatter counts attributed to the 511 keV events are subtracted from the prompt counts across the field of view to give true coincidence counts. This assumes that scattering is uniform throughout the FOV
However, in addition to the scatter caused by annihilation of the 511 keV gamma photons, other radiopharmaceuticals used in PET imaging may cause additional counts that the scatter model attempts to correct. For example, when using the radiopharmaceutical Rb-82 for imaging, approximately 14% of annihilation events occur with the prompt emission of a 777 keV gamma. The 777 keV annihilation events are realized in the measured data as a nearly flat background. The background effect caused by the 777 keV annihilation events is problematic to the conventional scatter correction model. More specifically, the conventional scatter correction model utilizes scaling between the scatter correction model output and the measured data to account for an absolute scaling of the scatter correction model to the measured data. Because the conventional scatter correction algorithm models use only the data representing the 511 keV annihilation events to estimate the scatter correction, the background effect caused by the 777 keV annihilation events causes a mis-scaling of the scatter correction. Therefore there is a need for a scatter correction model that accounts for both the 511 keV scatter events and the 777 keV annihilation events to improve the quality of a medical image.